Decision Support System for Predicting the Number of No-Show Passengers in Airline Industry
Airline decision about how many seats to allow to be overbooked is based on the expectation of the number of passengers who will not show up on a specific flight. This paper proposes a decision support system for predicting the number of no show passengers that combines the case-based reasoning (CBR...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2021-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/365671 |
| _version_ | 1797207025650761728 |
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| author | Nikola Vojtek* Bratislav Petrović Pavle Milošević |
| author_facet | Nikola Vojtek* Bratislav Petrović Pavle Milošević |
| author_sort | Nikola Vojtek* |
| collection | DOAJ |
| description | Airline decision about how many seats to allow to be overbooked is based on the expectation of the number of passengers who will not show up on a specific flight. This paper proposes a decision support system for predicting the number of no show passengers that combines the case-based reasoning (CBR) approach with Interpolative Boolean Algebra (IBA) and considers recommendations from both expert and algorithm. More precisely, recently proposed IBA similarity measure along with suitable aggregation operator is used for comparing alternatives in CBR algorithms. The proposed system was tested on the real-life data of the Belgrade-Amsterdam route. The obtained results show the necessity to include expert knowledge in the prediction process. Furthermore, the results are indicating that IBA-based models perform significantly better comparing to traditional distance-based models. The proposed expert system should contribute to an airline utilizing its inventory, which will further result in profit increase. |
| first_indexed | 2024-04-24T09:16:21Z |
| format | Article |
| id | doaj.art-be04a55f38964325b3e2241021aa8a19 |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:16:21Z |
| publishDate | 2021-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-be04a55f38964325b3e2241021aa8a192024-04-15T16:47:57ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392021-01-0128112313410.17559/TV-20191215144655Decision Support System for Predicting the Number of No-Show Passengers in Airline IndustryNikola Vojtek*0Bratislav Petrović1Pavle Milošević2University of Belgrade, Faculty of Organizational Sciences, Jove Ilića 154, Belgrade, 11000, SerbiaUniversity of Belgrade, Faculty of Organizational Sciences, Jove Ilića 154, Belgrade, 11000, SerbiaUniversity of Belgrade, Faculty of Organizational Sciences, Jove Ilića 154, Belgrade, 11000, SerbiaAirline decision about how many seats to allow to be overbooked is based on the expectation of the number of passengers who will not show up on a specific flight. This paper proposes a decision support system for predicting the number of no show passengers that combines the case-based reasoning (CBR) approach with Interpolative Boolean Algebra (IBA) and considers recommendations from both expert and algorithm. More precisely, recently proposed IBA similarity measure along with suitable aggregation operator is used for comparing alternatives in CBR algorithms. The proposed system was tested on the real-life data of the Belgrade-Amsterdam route. The obtained results show the necessity to include expert knowledge in the prediction process. Furthermore, the results are indicating that IBA-based models perform significantly better comparing to traditional distance-based models. The proposed expert system should contribute to an airline utilizing its inventory, which will further result in profit increase.https://hrcak.srce.hr/file/365671airline industrycase-based reasoningdecision support systemsinterpolative Boolean algebrano show passengers |
| spellingShingle | Nikola Vojtek* Bratislav Petrović Pavle Milošević Decision Support System for Predicting the Number of No-Show Passengers in Airline Industry Tehnički Vjesnik airline industry case-based reasoning decision support systems interpolative Boolean algebra no show passengers |
| title | Decision Support System for Predicting the Number of No-Show Passengers in Airline Industry |
| title_full | Decision Support System for Predicting the Number of No-Show Passengers in Airline Industry |
| title_fullStr | Decision Support System for Predicting the Number of No-Show Passengers in Airline Industry |
| title_full_unstemmed | Decision Support System for Predicting the Number of No-Show Passengers in Airline Industry |
| title_short | Decision Support System for Predicting the Number of No-Show Passengers in Airline Industry |
| title_sort | decision support system for predicting the number of no show passengers in airline industry |
| topic | airline industry case-based reasoning decision support systems interpolative Boolean algebra no show passengers |
| url | https://hrcak.srce.hr/file/365671 |
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